Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4948157 | Neurocomputing | 2016 | 11 Pages |
Abstract
In this brief, we study a class of memristor-based recurrent neural networks (MRNNs) with time-varying delays. Easily verifiable delay-independent criteria are established to ensure the existence and global exponential stability of periodic solutions by using novel analysis techniques, which not only improve but also complement some existing ones. These theoretical results are also supported with numerical simulations.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Lian Duan, Zhenyuan Guo,